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immunofluorescence. Familiarity with rodent models of diabetes, data analysis, and interpretation of complex biological datasets is essential. The candidate should demonstrate the ability to work independently
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data analysis for omics studies, including genotype data, bulk and single-cell RNA sequencing data, high-dimensional phenotype data, pathway and functional analysis, network analysis, polygenic risk
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, adapt and implement new lab procedures. Perform complex and routine molecular biology procedures including flow cytometric analysis, PCR, RT-PCR, Q-PCR, and Western blotting, DNA/RNA extraction
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genomic changes. In this role, the successful applicant will have the opportunity to participate in the analysis and interpretation of multi-omics datasets including whole genome sequencing, bulk and single
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analysis, basic scripting in R or Python, and integration of multi-omic datasets is considered an advantage. Candidates should also possess a strong publication record in high-impact journals and a
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molecular biological and quantitative techniques including microscopy, flow cytometry, computational/mathematical modeling, and utilizes approaches from synthetic biology and complex biological systems
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programs to perform analysis and produces written reports on results. Collects pilot data to help support new and competing renewal applications. Supervises undergraduate and graduate research students and
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. Genetic data analysis This is a core job profile description and is not reflective of all duties that may be assigned to a specific position in each individual department. The above statements are intended
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, solid phase extraction, etc.). Hands-on experience with different chromatographic separation and mass spectrometry methodologies for analysis of biomarkers, or small molecules. Education: Ph.D. in
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assays; viability assay; western blotting; comet assay; gH2AX stainig, DNA fiber assay; monoclonal antibody production and analysis). Abilities to work with small animals. Abilities to inoculate tumor